Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: Asian / Pacific Islander 
Marital status: Single 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Homemaker
Father's occupation: Homemaker
Hobbies: Listen to rock/indie music;Go to gigs;Exercise;Go to museums and galleries;Use social media 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Grammar checker (i.e., correcting grammar mistakes);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Microsoft Bing AI;Google Gemini 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation;Analyze data;Learning (e.g., explaining complex concepts in simple terms);Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Entertainment;Learning;Personal;Technical 
Prompt 1: Write me a short CV template that considers my admin background
Prompt 2: Write  me a meal plan for the next week for 1 person
Prompt 3: Write me a gym plan for the next 3 months for a newbie
Prompt 4: Give me a brief summary of the US election
Prompt 5: What crimes is Donald Trump guilty of?
Prompt 6: Write me a cove letter for a legal executive role
Prompt 7: Write me a brief summary of the recent plane crash in Kazakhstan
Prompt 8: Write me a brief summary of recent events in Ukraine
Prompt 9: Write me a covering letter for a restauraunt job
Prompt 10: Give me a brief summary of the UK local election process
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